Cost-effectiveness of monitoring endoxifen levels in breast cancer patients adjuvantly treated with tamoxifen.

PURPOSE: Breast cancer is the most common malignancy in women worldwide. Recurrence rates in breast cancer are considered to be dependent on the serum concentration of endoxifen, the active metabolite of tamoxifen. The goal of this study is to investigate the cost-effectiveness of periodically monitoring serum concentrations of endoxifen in adjuvant estrogen receptor alfa (ERα) positive breast cancer patients treated with tamoxifen in the Netherlands. METHODS: A Markov model with disease-free survival (DFS), recurrent disease (RD), and death states was constructed. The benefit of drug monitoring was modeled via a difference in the fraction of patients achieving adequate serum concentrations. Robustness of results to changes in model assumptions were tested through deterministic and probabilistic sensitivity analyses. RESULTS: Monitoring of endoxifen added 0.0115 quality-adjusted life-years (QALYs) and saved € 1564 per patient in the base case scenario. Deterministic sensitivity analysis demonstrated a large effect on the incremental cost-effectiveness ratio (ICER) of the differences in costs and utilities between the DFS and RD states. Probabilistic sensitivity analysis showed that the probability of cost-effectiveness at a willingness to pay of € 0 per quality-adjusted life-year (QALY) was 89.8%. CONCLUSIONS: Based on this model, monitoring of endoxifen in adjuvant ERα + breast cancer patients treated with tamoxifen is likely to add QALYs and save costs from a healthcare payer perspective. We advise clinicians to consider integrating serum endoxifen concentration monitoring into standard adjuvant tamoxifen treatment of ERα + breast cancer patients.

An Antiestrogenic Activity Score for tamoxifen and its metabolites is associated with breast cancer outcome.

PURPOSE: Endoxifen concentrations have been associated with breast cancer recurrence in tamoxifen-treated patients. However, tamoxifen itself and other metabolites also show antiestrogenic anti-tumor activity. Therefore, the aim of this study was to develop a comprehensive Antiestrogenic Activity Score (AAS), which accounts for concentration and antiestrogenic activity of tamoxifen and three metabolites. An association between the AAS and recurrence-free survival was investigated and compared to a previously published threshold for endoxifen concentrations of 5.97 ng/mL. PATIENTS AND METHODS: The antiestrogenic activities of tamoxifen, (Z)-endoxifen, (Z)-4-hydroxytamoxifen, and N-desmethyltamoxifen were determined in a cell proliferation assay. The AAS was determined by calculating the sum of each metabolite concentration multiplied by an IC50 ratio, relative to tamoxifen. The AAS was calculated for 1370 patients with estrogen receptor alpha (ERα)-positive breast cancer. An association between AAS and recurrence was investigated using Cox regression and compared with the 5.97 ng/mL endoxifen threshold using concordance indices. RESULTS: An AAS threshold of 1798 was associated with recurrence-free survival, hazard ratio (HR) 0.67 (95% confidence interval (CI) 0.47-0.96), bias corrected after bootstrap HR 0.69 (95% CI 0.48-0.99). The concordance indices for AAS and endoxifen did not significantly differ; however, using the AAS threshold instead of endoxifen led to different dose recommendations for 5.2% of the patients. CONCLUSIONS: Endoxifen concentrations can serve as a proxy for the antiestrogenic effect of tamoxifen and metabolites. However, for the aggregate effect of tamoxifen and three metabolites, defined by an integrative algorithm, a trend towards improving treatment is seen and moreover, is significantly associated with breast cancer recurrence.

Pharmacokinetics and excretion of 14C-Plitidepsin in patients with advanced cancer.

Plitidepsin (Aplidin®) is a marine-derived anticancer compound currently investigated in phase III clinical trials. This article describes the distribution, metabolism and excretion of this novel agent and it mainly aims to identify the major routes of elimination. Six subjects were enrolled in a mass balance study during which radiolabelled plitidepsin was administered as a 3-h intravenous infusion. Blood samples were taken and urine and faeces were collected. Total radioactivity (TRA) analysis using Liquid Scintillation Counting (LSC) was done to determine the amount of radioactivity excreted from the body and plitidepsin concentrations in whole blood, plasma and urine were determined by validated liquid chromatography-tandem mass spectrometry (LC-MS/MS) assays. In total, a mean of 77.4% of the administered radioactivity was excreted over a time period of 20 days, of which 71.3% was recovered in faeces and 6.1% was found in urine. The majority excreted in urine was accounted for by unchanged plitidepsin, with only 1.5% of the total administered dose explained by metabolites in urine. Faeces, on the other hand contained low levels of parent compound, which means that most of the TRA excreted in faeces was accounted for by metabolites. TRA levels were 3.7 times higher in whole blood compared to plasma. Plitidepsin was widely distributed and plasma clearance was low. This study shows that red blood cells are a major distribution compartment and that the biliary route is the main route of total radioactivity excretion.

Pharmacodynamic modeling of adverse effects of anti-cancer drug treatment.

PURPOSE: Adverse effects related to anti-cancer drug treatment influence patient's quality of life, have an impact on the realized dosing regimen, and can hamper response to treatment. Quantitative models that relate drug exposure to the dynamics of adverse effects have been developed and proven to be very instrumental to optimize dosing schedules. The aims of this review were (i) to provide a perspective of how adverse effects of anti-cancer drugs are modeled and (ii) to report several model structures of adverse effect models that describe relationships between drug concentrations and toxicities. METHODS: Various quantitative pharmacodynamic models that model adverse effects of anti-cancer drug treatment were reviewed. RESULTS: Quantitative models describing relationships between drug exposure and myelosuppression, cardiotoxicity, and graded adverse effects like fatigue, hand-foot syndrome (HFS), rash, and diarrhea have been presented for different anti-cancer agents, including their clinical applicability. CONCLUSIONS: Mathematical modeling of adverse effects proved to be a helpful tool to improve clinical management and support decision-making (especially in establishment of the optimal dosing regimen) in drug development. The reported models can be used as templates for modeling a variety of anti-cancer-induced adverse effects to further optimize therapy.